Abstract
In this abstract new ESA SEOM project is presented, which will start in January 2017.
The main objective of this research is to develop, analyze and validate novel methodologies for land cover and vegetation mapping using time series of Sentinel-1 data and in particular by exploiting the temporal evolution of the interferometric coherence. Further the project aims on quantifying the impact and possible benefit of using Sentinel-1 InSAR (Interferometric Synthetic Aperture Radar) data relative to traditional land cover and vegetation mapping using optical data (especially Sentinel-2) and traditional intensity-based SAR (Synthetic Aperture Radar) approaches.
The main classes sought after are Forests, Agricultural areas (e.g. Crops), Artificial surfaces (e.g. Urban), Water Bodies, Scrub and Herbaceous Vegetation, Open or bare land with little to no vegetation and Wetlands.
We have setup three different reference test areas with very accurate ground truth data for performing quantitative assessment and validation in Spain, Italy and Poland.
In order to scientifically evaluate the performance of different methodologies for land cover and vegetation mapping a round robin is organized. Participants will get access to pre-processed datasets over the three study areas together with some access for relevant training data for classification purposes. Further participants will also get access to processing facilities via a private cloud platform hosted at EURAC Research. The kickoff for this round robin will be in April 2017 and it will stay active for 4-6 month.